NEW YORK (SpeechTEK 2011) — “There’s too much data,” laments Amanda Harlan, lead technical account manager at Microsoft Tellme, during Monday’s “Best Practices for Using Analytics” breakout session at SpeechTEK 2011 in New York City. “It’s hard to get through the data to interesting insights. We’ve created roadblocks for ourselves.”

One of the overarching themes in speech analytics this year has been the proliferation of data, a phenomenon that has become so prevalent in the past decade that companies have been carting it away by the shovelful. Harlan reports that Microsoft Tellme processes about 100 calls per second, produces more than 3 terabytes of data a week, and processes 11 billion utterances a year. That’s a deep reserve and it can produce a sense of security that can be harmful if it is misguided, many of Monday’s speakers asserted.

“United Breaks Guitars”—a now infamous story in customer-relationship management circles that it has been recounted at the last three SpeechTEK conferences—provides a case in point. This year, Daniel Ziv, vice president of interactions for Verint Systems, used it illustrate how a company might be misled by its own data in the “Make Better Decisions With Multichannel Analytics” session.

“There was a lot of data around how much luggage was lost [or damaged] and United had great numbers,” Ziv says. “It was less than half a percent. They were better off than most airlines. The structured data was saying we don’t need to deal with this. But there were 300,000 calls coming in about lost luggage.It was an emotional issue—more than cancelled flights.”

In short, United failed to account for the level of emotional upset associated with lost and damaged luggage because it was statistically negligible. As a consequence, the company had not prioritized appeasing the 0.5 percent of customers who were aggrieved. In a social media world, this had disastrous CRM consequences because one guy, Dave Carroll, had his guitar broken and wrote a hit song about it, “United Breaks Guitars.” None of that could be anticipated without targeted drilling into the data.

Dan York, director of conversations at Voxeo, provided another example in his talk. He points to a 2010 Opus Research consumer preference study about whether customers wanted to receive order status and delivery updates via short message service (SMS) texts that found that nearly 35 percent of respondents aged 18 to 24 registered a strong interest, while more than 35 percent of those aged 44 to 54 posted a strong aversion. The results between the two age groups are nearly mirror inverses. If you were looking at overall averages, you’d never know that, though. Without the demographic breakdown, the real narrative is lost, and that could have serious repercussion for a business that was making decisions about how to allocate resources across channels. In other words, data will do you no good if you can’t read it. Data is only as good as the actionable items it produces.

One of the big actionables success stories on display at the breakout sessions was that of Teligence, a Nexidia case study. Teligence is a “voice-enabled social network provider”—basically it operates a number of party or dating lines. According to Camilo Bandera-Ortega, a former contact center manager and now general manager of On-Q Global Solutions, the firm manages 60,000 calls per month. Somewhere between 30 and 40 percent of these calls were non-revenue-generating. Many of these callers had questions about the service but they had intention of buying. Many would call several times a day. Using Nexidia’s analytics, Teligence was able to identify these and the questions they commonly asked. Bandera-Ortega made the decision to address their questions in the IVR and then prevent non-paying callers from getting an agent. The result freed up precious call center resources and saved the company a pile of cash.